Unique value based on for loop-CodePudding

Having a data frame as below:

data = {'Name':['Mathew', 'Mathew', 'Mathew', 'Mathew','Mathew','John','John','John'],
        'Age':[12,12, 12,13, 13,12,13,13],
       'Colour':['Yellow','Blue','Yellow','green','blue','pink','black','brown']}
df = pd.DataFrame(data)
df

I tried a loop as below. I need the unique value in based on the loop. Like, Name is mathew and age is 12, mylist contain the values yellow and blue.

for j in set(df.Name):
            for i in set(df.Age):
                #my_list=list of unique colour produced in according to each loop
                    print(i,j)

output of above code will be as follows:

12 John
13 John
12 Mathew
13 Mathew

But what i want as output is,df.Name is mathew and df.age is 12, then mylist will be as follows: my_list=['yellow','blue']

CodePudding user response：

Here is your solution in a for loop:

for name in set(df['Name']):
    for age in set(df['Age']):
        print(name, age)
        my_list = df.loc[(df['Name']==name) & (df['Age']==age),'Colour'].unique().tolist()
        print(my_list,'\n')

Output:

Mathew 12
['Yellow', 'Blue'] 

Mathew 13
['green', 'blue'] 

John 12
['pink'] 

John 13
['black', 'brown']

other approaches:

out = df.groupby(['Name','Age'])['Colour'].unique()
print(out)

Output:

Name    Age
John    12             [pink]
        13     [black, brown]
Mathew  12     [Yellow, Blue]
        13      [green, blue]
Name: Colour, dtype: object

To make it a bit more clear, since you seem to be a bit confused. out is a pd.Series where you have for each index (which is a pair of name and age) all unqiue colors as an array.

Since you really want single lists as output, here you go:

John12, John13, Mathew12, Mathew13 = df.groupby(['Name','Age'])['Colour'].apply(lambda x: list(np.unique(x)))

print(John12)
print(John13)
print(Mathew12)
print(Mathew13)

Now you have 4 single lists for each combination, which you can use anywhere else.

['pink']
['black', 'brown']
['Blue', 'Yellow']
['blue', 'green']